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transforEmotion  

Sentiment Analysis for Text, Image and Video using Transformer Models
View on CRAN: Click here


Download and install transforEmotion package within the R console
Install from CRAN:
install.packages("transforEmotion")

Install from Github:
library("remotes")
install_github("cran/transforEmotion")

Install by package version:
library("remotes")
install_version("transforEmotion", "0.1.7")



Attach the package and use:
library("transforEmotion")
Maintained by
Aleksandar Tomašević
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-03-01
Latest Update: 2025-05-15
Description:
Implements sentiment analysis using huggingface <https://huggingface.co> transformer zero-shot classification model pipelines for text and image data. The default text pipeline is Cross-Encoder's DistilRoBERTa <https://huggingface.co/cross-encoder/nli-distilroberta-base> and default image/video pipeline is Open AI's CLIP<https://huggingface.co/openai/clip-vit-base-patch32>. All other zero-shot classification model pipelines can be implemented using their model name from <https://huggingface.co/models?pipeline_tag=zero-shot-classification>.
How to cite:
Aleksandar Tomašević (2022). transforEmotion: Sentiment Analysis for Text, Image and Video using Transformer Models. R package version 0.1.7, https://cran.r-project.org/web/packages/transforEmotion. Accessed 06 Jun. 2026.
Previous versions and publish date:
0.0.1 (2022-03-01 22:10), 0.1.0 (2022-04-04 23:40), 0.1.1 (2022-05-11 14:30), 0.1.4 (2024-01-09 13:40), 0.1.5 (2024-08-20 14:20), 0.1.6 (2025-05-15 12:10)
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Complete documentation for transforEmotion
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